U.S. patent application number 09/935678 was filed with the patent office on 2002-03-07 for method for detecting physiological condition of sleeping patient based on analysis of pulse waves.
Invention is credited to Hayano, Junichiro, Kimura, Teiyuu, Nanba, Shinji, Ohsaki, Rie, Shiomi, Toshiaki.
Application Number | 20020029000 09/935678 |
Document ID | / |
Family ID | 26599437 |
Filed Date | 2002-03-07 |
United States Patent
Application |
20020029000 |
Kind Code |
A1 |
Ohsaki, Rie ; et
al. |
March 7, 2002 |
Method for detecting physiological condition of sleeping patient
based on analysis of pulse waves
Abstract
A physiological condition detecting method detects pulse waves
from the body of a patient, and creates the envelope of the pulse
waves by connecting every peak of the pulse waves. It determines
that the patient is in non-REM sleep, if the envelope fluctuates
regularly. It determines that the patient is in REM sleep, if the
envelope fluctuates irregularly. Further the method calculates and
normalizes the amplitude and period of the envelope. It determines
whether the patient has obstructive sleep apnea syndrome based on
the normalized amplitude. It determines whether the patient has
central sleep apnea syndrome based on the normalized period. It
determines that the patient has mixed sleep apnea syndrome based on
the normalized amplitude and the normalized period.
Inventors: |
Ohsaki, Rie; (Anjo-city,
JP) ; Kimura, Teiyuu; (Nagoya-city, JP) ;
Nanba, Shinji; (Kariya-city, JP) ; Hayano,
Junichiro; (Nagoya-city, JP) ; Shiomi, Toshiaki;
(Nagoya-city, JP) |
Correspondence
Address: |
LAW OFFICE OF DAVID G POSZ
2000 L STREET, N.W.
SUITE 200
WASHINGTON
DC
20036
US
|
Family ID: |
26599437 |
Appl. No.: |
09/935678 |
Filed: |
August 24, 2001 |
Current U.S.
Class: |
600/500 |
Current CPC
Class: |
A61B 5/02416
20130101 |
Class at
Publication: |
600/500 |
International
Class: |
A61B 005/02 |
Foreign Application Data
Date |
Code |
Application Number |
Sep 7, 2000 |
JP |
2000-271456 |
Nov 17, 2000 |
JP |
2000-351713 |
Claims
What is claimed is:
1. A method for detecting a physiological condition of a patient
comprising the steps of: detecting pulse waves from the patient's
body; creating an envelope of the pulse waves; analyzing the
envelope; and determining whether the patient is in a specific
physiological condition based on a result of the analysis.
2. A method for detecting a physiological condition of a patient as
in claim 1, wherein the step of analyzing includes the step of:
calculating for every regular time interval a statistical index
which represents characteristics of the envelope over the time
interval, and wherein the step of determining uses the statistical
index.
3. A method for detecting a physiological condition of a patient
comprising the steps of: detecting pulse waves from the patient's
body; calculating a pulse height of each of the pulse waves;
analyzing the pulse height; and determining whether the patient is
in a specific physiological condition based on a result of the
analysis.
4. A method for detecting a physiological condition of a patient as
in claim 3, wherein the step of analyzing includes the step of:
calculating for every regular time interval a statistical index
which represents characteristics of the pulse height over the time
interval, and wherein the step of determining uses the statistical
index.
5. A method for detecting a physiological condition of a patient as
in claim 3, wherein the step of analyzing includes the steps of:
creating a baseline of the pulse waves by connecting middle points
of the pulse height; and calculating for every regular time
interval a statistical index which represents characteristics of
the baseline over the time interval, and wherein the step of
determining uses the statistical index.
6. A method for detecting a sleep condition of a patient comprising
the steps of: detecting pulse waves from the sleeping patient's
body; creating an envelope of the pulse waves by connecting one of
tops and bottoms of the pulse waves; determining that the patient
is in non-REM sleep if the envelope fluctuates regularly; and
determining that the patient is in REM sleep if the envelope
fluctuates irregularly.
7. A method for detecting a sleep condition of a patient comprising
the steps of: detecting pulse waves from the sleeping patient's
body; calculating a pulse height of each of the pulse waves;
determining that the patient is in non-REM sleep if the pulse
height fluctuates regularly; and determining that the patient is in
REM sleep if the pulse height fluctuates irregularly.
8. A method for detecting a sleep condition of a patient comprising
the steps of: detecting pulse waves from the sleeping patient's
body; calculating a pulse height of each of the pulse waves;
creating a baseline of the pulse waves by connecting middle points
of the pulse height; determining that the patient is in non-REM
sleep if the baseline fluctuates regularly; and determining that
the patient is in REM sleep if the baseline fluctuates
irregularly.
9. A method for detecting a sleep condition of a patient as in
claim 6 further comprising the step of: calculating for every
regular time interval a statistical index which represents
characteristics of the envelope over the time interval, wherein the
steps of determining use the statistical index.
10. A method for detecting a sleep condition of a patient as in
claim 7 further comprising the step of: calculating for every
regular time interval a statistical index which represents
characteristics of the pulse height over the time interval, wherein
the steps of determining use the statistical index.
11. A method for detecting a sleep condition of a patient as in
claim 8 further comprising the step of: calculating for every
regular time interval a statistical index which represents
characteristics of the baseline over the time interval, wherein the
steps of determining use the statistical index.
12. A method for detecting a sleep condition of a patient as in
claim 9, wherein the statistical index includes at least one of an
average, a maximum value, a minimum value, a variance, a deviation
of a level of the envelope.
13. A method for detecting a sleep condition of a patient as in
claim 10, wherein the statistical index includes at least one of an
average, a maximum value, a minimum value, a variance, a deviation
of the pulse height.
14. A method for detecting a sleep condition of a patient as in
claim 11, wherein the statistical index includes at least one of an
average, a maximum value, a minimum value, a variance, a deviation
of a level of baseline.
15. A method for detecting a physiological condition of a patient
as in claim 6, wherein the pulse waves are detected from one of the
patient's wrist and forearm.
16. A method for detecting a sleep condition of a patient as in
claim 7, wherein the pulse waves are detected from one of the
patient's wrist and forearm.
17. A method for detecting a sleep condition of a patient as in
claim 8, wherein the pulse waves are detected from one of the
patient's wrist and forearm.
18. A method for diagnosing a patient as sleep apnea syndrome
comprising the steps of: detecting pulse waves from the sleeping
patient's body; analyzing the pulse waves; and determining whether
the patient has sleep apnea syndrome based on a result of the
analysis.
19. A method for diagnosing a patient as sleep apnea syndrome as in
claim 18 further comprising the step of: determining whether a type
of the sleep apnea syndrome is obstructive sleep apnea based on the
result of the analysis.
20. A method for diagnosing a patient as sleep apnea syndrome as in
claim 18 further comprising the step of: determining whether a type
of the sleep apnea syndrome is central sleep apnea based on the
result of the analysis.
21. A method for diagnosing a patient as sleep apnea syndrome as in
claim 18 further comprising the step of: determining whether a type
of the sleep apnea syndrome is mixed sleep apnea.
22. A method for diagnosing a patient as sleep apnea syndrome as in
claim 19, wherein the step of analyzing creates an envelope of the
pulse waves by connecting one of tops and bottoms of the pulse
waves and calculates a degree of fluctuation of the envelope, and
wherein the steps of determining determine that the patient has
obstructive sleep apnea syndrome if the degree of the fluctuation
of the envelope exceeds a predetermined level.
23. A method for diagnosing a patient as sleep apnea syndrome as in
claim 19, wherein the step of analyzing calculates a degree of
fluctuation of peaks of the pulse waves, and wherein the steps of
determining determine that the patient has obstructive sleep apnea
syndrome if the degree of the fluctuation of the peaks exceeds a
predetermined level.
24. A method for diagnosing a patient as sleep apnea syndrome as in
claim 19, wherein the step of analyzing calculates a pulse height
of each of the pulse wave and a degree of fluctuation of the pulse
height, and wherein the steps of determining determine that the
patient has obstructive sleep apnea syndrome if the degree of the
fluctuation of the pulse height exceeds a predetermined level.
25. A method for diagnosing a patient as sleep apnea syndrome as in
claim 19, wherein the step of analyzing calculates a pulse area
which is defined by each of the pulse waves, and a degree of
variation of the pulse area, and wherein the steps of determining
determine that the patient has obstructive sleep apnea syndrome if
the degree of the variation of the pulse area exceeds a
predetermined level.
26. A method for diagnosing a patient as sleep apnea syndrome as in
claim 19, wherein the step of analyzing calculates a pulse length
which is a length of each of the pulse waves, and a degree of
variation of the pulse length, and wherein the steps of determining
determine that the patient has obstructive sleep apnea syndrome if
the degree of the variation of the pulse length exceeds a
predetermined level.
27. A method for diagnosing a patient as sleep apnea syndrome as in
claim 19, wherein the steps of determining use fluctuation of the
pulse waves.
28. A method for diagnosing a patient as sleep apnea syndrome as in
claim 19, wherein the step of analyzing creates a first envelope of
the pulse wave which connects tops of the pulse waves and a second
envelope of the pulse waves which connects bottoms of the pulse
waves, wherein the step of analyzing further calculates a closeness
of one of bottoms of the first envelope and corresponding one of
tops of the second envelope, and wherein the steps of determining
determine that the patient has obstructive sleep apnea syndrome if
the closeness exceeds a predetermined level.
29. A method for diagnosing a patient as sleep apnea syndrome as in
claim 27, wherein the step of analyzing calculates a difference
between the fluctuation of the pulse waves and fluctuation of pulse
waves detected from the patient in an eupneic condition, and
wherein the steps of determining determine that the patient has
obstructive sleep apnea syndrome if the degree of the difference
exceeds a predetermined level.
30. A method for diagnosing a patient as sleep apnea syndrome as in
claim 20, wherein the step of analyzing creates an envelope of the
pulse waves by connecting one of tops and bottoms of the pulse
waves, and calculates a period of fluctuation of the envelope, and
wherein the steps of determining determine that the patient has
central sleep apnea syndrome if the period exceeds a predetermined
length.
31. A method for diagnosing a patient as sleep apnea syndrome as in
claim 21, wherein the step of determining whether the patient has
sleep apnea syndrome detects obstructive sleep apnea condition and
central sleep apnea condition based on the result of analysis, and
wherein the step of determining the type of the sleep apnea
syndrome determines that the patient has mixed sleep apnea syndrome
if the obstructive sleep apnea condition is detected after the
central sleep apnea condition is detected.
32. An apparatus for detecting a physiological condition of a
patient comprising: a pulse sensor for detecting pulse waves from
the patient body; a drive circuit for driving the pulse sensor; a
data processing unit for executing a program for creating and
analyzing an envelope of the pulse waves and detecting a
physiological condition based on a result of the analysis; and a
display unit for displaying a result of the detection.
33. An apparatus for detecting a physiological condition of a
patient as in claim 32, wherein the pulse sensor is designed to be
worn on one of the patient's wrist and finger.
34. An apparatus for detecting a physiological condition of a
patient as in claim 32, wherein the pulse waves are detected from
the sleeping patient, and wherein the data processing unit executes
the program for detecting a sleep condition of the patient based on
the result of the analysis.
35. An apparatus for detecting a physiological condition of a
patient as in claim 32, wherein the pulse waves are detected from
the sleeping patient, and wherein the data processing unit executes
the program for detecting a respiratory condition of the patient
based on the result of the analysis.
Description
CROSS REFERENCE TO RELATED APPLICATION
[0001] This application is based on and incorporates herein by
reference Japanese Patent Applications No. 2000-271456 filed on
Sep. 7, 2000 and NO. 2000-351713 filed on Nov. 17, 2000.
BACKGROUND OF THE INVENTION
[0002] 1. Field of the Invention
[0003] The present invention relates to a method for detecting the
physiological condition of a sleeping patient.
[0004] 2. Related Art
[0005] The sleep condition (depth of a sleep) of a patient is
usually detected from a polysomnogram which shows signals which are
simultaneously measured on the patient's body by a
polysomnographer. The polysomnogram includes an
electroencephalogram, an oclogram, an electromyogram, an
electrocardiogram and the like. The patient needs to be
hospitalized for such measurement, because the polysomnographer is
a large-sacaled facility. Further the patient feels uncomfortable
during the measurement, because sensors are attached on his/her
head and face. Accordingly the patient's sleep is disturbed and, as
a result, accurate data is not obtained.
[0006] JP-A-3-41926 discloses an alternative method for detecting a
sleep condition of a patient. The method detects a respiration rate
and a pulse rate of the patient, and determines the patient's sleep
condition based on the detected respiration rate and pulse rate as
follows. The Pulse period, which correspond to the R-R period in
the electrocardiogram, is calculated, and thereafter the sleep
condition (REM sleep or non-REM sleep) is detected from the
fluctuation of the pulse period. In order to obtain the pulse
period, the peak (top or bottom) of every pulse wave should be
accurately detected. When pulse waves fluctuate regularly, the
peaks of the pulse waves can be detected accurately. However, pulse
waves may fluctuate irregularly if the patient moves his/her body
during sleep. In this case, the peaks of pulse waves may shift due
to a factor other than the fluctuation of blood flow and
consequently be misdetected. In order to obtain the pulse period
based on the peaks of the pulse waves which may be provided as the
result of the misdetection, complicated calculations are required.
Accordingly this method cannot readily detect the patient's sleep
condition.
[0007] Further, the pulse period varies distinctly depending on
whether the patient is in the REM sleep or non-REM sleep, only when
the patient is healthy. When the patient is ill or old, the pulse
period varies only slightly depending on whether the patient is in
the REM sleep or non-REM sleep. Accordingly it is difficult to
detect the sleep condition.
[0008] The diagnosis of sleep apnea syndrome is also made by
examining all the signals in the polysomnogram. Therefore it is
expensive and requires time and effort for a patient to have
examination for sleep apnea syndrome, because the patient needs to
be hospitalized. As a result, it is difficult to detect and treat
the sleep apnea syndrome early.
SUMMARY OF THE INVENTION
[0009] The present invention has an object to provide a method for
accurately detecting the sleep condition of a patient at home
without executing complicated calculation and without being
affected by noise due to the movement of the patient's body.
[0010] The present invention also has an object to provide a method
for diagnosing sleep apnea syndrome (SAS) at home without imposing
a burden on a patient.
[0011] A first method according to the present invention detects
the sleep condition of a patient by analyzing the pulse waves of
the patient. The first method measures pulse waves on the patient's
body, and creates the envelope of the pulse waves by connecting the
tops and bottoms of the pulse waves. The first method determines
that the patient is in non-REM sleep, if the created envelope
fluctuates regularly. It determines that the patient is in REM
sleep, if the created envelope fluctuates irregularly.
[0012] The pulse height, which is a height of every pulse wave, or
the baseline, which is a line connecting a middle point of every
pulse wave, may be created instead of the envelope of the pulse
waves. In this case, it is determined that the patient is in
non-REM sleep, if the created pulse height or baseline fluctuates
regularly. It is determined that the patient is in REM sleep, if
the created pulse height or baseline fluctuates irregularly.
[0013] A second method according to the present invention diagnoses
a patient as SAS by analyzing the pulse waves of the patient. The
second method measures pulse waves on the patient's body, and
analyzes the pulse wave data. Based on the result of the analysis,
the second method determines whether the patient has SAS.
Preferably, the type of the SAS is also determined based on the
result of the analysis, if it is determined that the patient has
SAS.
BRIEF DESCRIPTION OF THE DRAWINGS
[0014] The above and other objects, features and advantages of the
present invention will become more apparent from the following
detailed description made with reference to the accompanying
drawings. In the drawings
[0015] FIG. 1 is a schematic diagram of an apparatus for detecting
the physiological condition of a patient;
[0016] FIG. 2 is a flowchart of a process for detecting the sleep
condition of a patient according to a first embodiment;
[0017] FIG. 3 is a graph of pulse waves detected from a
patient;
[0018] FIGS. 4A and 4B are graphs of envelopes of pulse waves
detected from the patient in REM sleep and in non-REM sleep,
respectively;
[0019] FIG. 5 is a graph of the envelopes, pulse height and
baseline of pulse waves while pulse period fluctuates
regularly;
[0020] FIG. 6 is a graph of the envelopes, pulse height and
baseline of pulse waves while pulse period fluctuates
irregularly;
[0021] FIG. 7 is a flowchart of a process for diagnosing sleep
apnea syndrome according to a second embodiment;
[0022] FIG. 8 is a graph of pulse waves detected from a patient in
eupneic condition;
[0023] FIG. 9 is a graph of pulse waves detected from a patient in
obstructive sleep apnoeaic condition;
[0024] FIG. 10 is a graph of pulse waves detected from a patient in
central sleep apnoeaic condition;
[0025] FIG. 11 is a flowchart of a process for detecting the sleep
condition of a patient according to a modification of the first
embodiment;
[0026] FIG. 12 is a flowchart of a process for detecting the sleep
condition of a patient according to another modification of the
first embodiment;
[0027] FIGS. 13A-13C are graphs of pulse waves detected from the
patient in eupneic condition, the patient in obstructive sleep
apnoeaic condition, and the patient in central sleep apnoeaic
condition (enlargements of FIGS. 8, 9, and 10) respectively;
and
[0028] FIGS. 14A-14C are graphs of pulse waves detected from the
patient in eupneic condition, the patient in obstructive sleep
apnoeaic condition, and the patient in central sleep apnoeaic
condition (enlargements of FIGS. 13A-13C) respectively.
DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENT
[0029] (First Embodiment)
[0030] A method according to a first embodiment detects the sleep
condition of a patient by a physiological condition detection
apparatus shown in FIG. 1. The physiological condition detection
apparatus includes a pulse wave sensor 1, a drive circuit 2, a data
processing unit 3, and a display unit 4. The data processing unit 3
includes a detection circuit 3A, an A/D converter 3B, and a
microcomputer 3C. The pulse wave sensor 1 is a well-known optical
sensor, and worn on the patient's wrist 5 or finger. The sensor 1
includes a sensor housing 1b on which a window 1a is formed. The
sensor 1 further includes a light emitting element 1c and a light
receiving element 1d in the housing 1b. The drive circuit 2 drives
the light emitting element 1c to emit light towardthepatient's
wrist 5. A portion of the emitted light penetrates the capillary
arteriole 6 in the inside of the patient's wrist 5 and is absorbed
by the haemoglobin in the blood. The rest of the emitted light is
reflected and scattered by the capillary arteriole 6, and partly
reaches the light receiving element 1d. As the amount of the
haemoglobin in the blood fluctuates in waves due to the pulsation
of the patient's blood, the amount of the light absorbed by the
haemoglobin also fluctuates in waves. As a result, the amount of
the light which is reflected by the capillary arteriole 6 and
reaches the light receiving element id fluctuates in waves. This
fluctuation in the amount of the light received by the light
receiving element id is detected as pulse wave information. The
pulse wave sensor 1 further converts the pulse wave information
into electrical signals (i.e., voltage signals), and outputs the
electrical signals to the data processing unit 3.
[0031] In the data processing unit 3, the detection circuit 3A
receives and amplifies the electrical signals. The A/D converter 3B
converts the amplified analog signals to digital signals at a
sampling frequency of 100 Hz. The digital signals are outputted to
the microcomputer 3C. The microcomputer 3C is programmed to detect
the sleep condition of the patient by using the digital signals
which represent pulse wave information detected from the sleeping
patient as follows.
[0032] Referring to FIG. 2, pulse wave data is measured from the
digital signals at step 10. The pulse wave data is filtered through
a digital filter so that unwanted frequency component of the pulse
waves are eliminated at step 20. The peak of every pulse wave is
detected from the pulse wave data at step 30.
[0033] One of the envelopes of the pulse waves is created at step
40. FIG. 3 shows pulse waves detected from the patient. Two
envelopes A, B can be created by connecting the peaks of the pulse
waves as shown in FIG. 3. One envelope A is obtained by connecting
the tops of the pulse waves, while the other envelope B is obtained
by connecting the bottoms of the pulse waves. Either of the
envelopes A, B may be created at step 40. FIGS. 4A and 4B show the
envelopes of the pulse waves detected during the patient's REM
sleep and non-REM sleep, respectively.
[0034] At step 50, the characteristics of the envelope A, B is
detected at regular intervals as follows. A statistical index such
as the average, maximum value, minimum value, variance, deviation
or the like is employed for representing the characteristics of the
envelope A, B over an interval. The employed index is calculated
over and at regular intervals (i.e., 20 seconds) at step 50. At
step 60, the sleep condition of the patient is detected based on
the fluctuation of the calculated index. As shown in FIG. 5, the
envelopes A, B fluctuate regularly while the pulse period
fluctuates regularly. As shown in FIG. 6, the envelopes A, B
fluctuate irregularly while the pulse period fluctuates
irregularly. It is known that the patient is in non-REM sleep if
the pulse period fluctuates regularly. It is also known that the
patient is in REM sleep if the pulse period fluctuates
irregularly.
[0035] Further the envelopes A, B of the pulse waves actually
fluctuate more irregularly during the patient's REM sleep than
during the patient's non-REM sleep as shown in FIGS. 4A and 4B. In
the case of non-REM sleep, the standard deviations calculated from
the envelope data shown in FIG. 4B over intervals of 20 seconds are
0.15 (0-20 s), 0.16 (20-40 s) and 0.16 (40-60 s). That is, the
standard deviations do not vary largely. In contrast to this, in
the case of REM sleep, the standard deviations calculated from the
envelope data shown in FIG. 4A over intervals of 20 seconds are
0.16 (0-20 s), 0.09 (20-40 s), 0.10 (40-60 s) and 0.15 (60-80 s).
That is, the standard deviations vary largely. Therefore it may be
determined that the patient is in non-REM sleep, if the envelope A,
B flucutates regularly, that is, the statistical index varies
within the predetermined range. Further it may be determined that
the patient is in REM sleep, if the envelope A, B fluctuates
irregularly, that is, the statistical index varies exceeding the
predetermined range.
[0036] Accordingly, it is determined at step 60 that the patient is
in REM sleep, if the variation of the index is within 25%. Further
it is determined at step 60 that the patient is in non-REM sleep,
if the variation of the index is over 25%. The detected sleep
condition is displayed by the display unit 4 at step 70.
[0037] (Second Embodiment)
[0038] A method according to a second embodiment diagnoses a
patient as sleep apnea syndrome (SAS) by a physiological condition
detection apparatus (shown in FIG. 1) which has the similar
configuration as the first embodiment. Further the method
determines the type of SAS. The type of SAS is obstructive sleep
apnea syndrome (OSAS), central sleep apnea syndrome (CSAS), or
mixed sleep apnea syndrome (MSAS). In obstructive sleep apnoeaic
(OSA) condition, the breathing movement of the patient's thoracic
part and abdominal wall is maintained, but ventilation through the
patient's mouth or nose is stopped due to partially obstructed
upper airway. In central sleep apnoeaic (CSA) condition, movement
of the patient's respiratory muscle is stopped due to a standstill
of respiratory center or a disturbance of excitation-conduction.
The patient is diagnosed as MSAS if he/she shifts from CSA
condition to OSA condition.
[0039] In the physiological condition detection apparatus,
similarly to the first embodiment, a pulse sensor 1 is driven by a
drive circuit 2 and detects pulse wave information from the
patient's body. The pulse sensor 1 outputs the pulse wave
information as electrical signals to a data processing unit 3. In
the data processing unit 3, a detection circuit 3A and an A/D
converter 3B operates similarly to the first embodiment, and a
microcomputer 3C receives digital signals from the A/D converter
3B. The microcomputer 3C is programmed to diagnose the patient as
SAS by using the digital signals which represents the pulse wave
information detected from the sleeping patient as follows.
[0040] Referring to FIG. 7, the received digital signals are
processed at steps 10-30 and one of the envelopes A, B of the pulse
waves is created at step 40 similarly to the first embodiment.
However, both of the envelopes A, B may be created at step 40, if
necessary at later steps.
[0041] FIG. 8 shows pulse waves detected from the patient in
eupneic condition, and FIG. 9 shows pulse waves detected from the
patient in OSA condition. The envelopes A, B shown in FIG. 9
fluctuate largely as compared with the envelopes A, B shown in FIG.
8. Specifically, the normalized amplitude of the envelope A, B
(FIG. 9) in OSA condition is twice the normalized amplitude of the
envelope A, B (FIG. 8) in eupneic condition or higher. Accordingly
the amplitude of the envelope A, B is calculated at step 50A for
detecting OSA condition. The calculated amplitude is normalized
with respect to the amplitude of the pulse wave, because the
amplitude of the envelope changes in proportion to the amplitude of
the pulse wave. For example, the amplitude of the envelope is
normalized by being divided by the amplitude of the pulse wave
averaged over one period of the pulse waves.
[0042] FIG. 10 shows pulse waves detected from the patient in CSA
condition. In CSA condition, movement of the patient's thoracic
part is stopped. Therefore pulse wave data detected from the
patient in CSA condition does not include signals which represent
respiration. Accordingly, the envelope A, B fluctuates in a long
period as shown in FIG. 10. Specifically, it fluctuates in a period
of roughly 10 seconds (7-12 seconds). In contrast to this, the
envelope A, B in eupneic condition or OSA condition does not
fluctuate in a long period as shown in FIG. 8 or 9. Therefore the
period of the fluctuation of the envelope A, B is calculated at
step 50B for detecting CSA condition. The calculated period is also
normalized.
[0043] At step 60A, it is determined that the patient is in OSA
condition if the normalized amplitude of the envelope A, B is twice
that in the eupnea condition or higher. At step 60B, it is
determined that the patient is in CSA condition if the normalized
period is equal to or longer than 7 seconds.
[0044] At step 70A, a diagnosis of SAS is made based on the results
of steps 60A and 60B. Further the type of SAS is determined based
on the results of steps 60A and 60B, if the patient is diagnosed as
SAS. The patient is diagnosed as MSAS, if he/she shifts from CSA
condition to OSA condition. The result of the diagnosis is
displayed by the display unit 4.
[0045] (Modifications)
[0046] In the first embodiment, the sleep condition of the patient
may be detected based on the pulse height of the pulse waves as
shown in FIG. 11. The pulse height is defined as the height of a
pulse wave as shown in FIG. 3. The pulse height of every pulse wave
is created instead of the envelope A, B at step 40. Further
statistical index which represents the characteristics of pulse
height is calculated over and at regular intervals at step 50. As
shown in FIG. 4, the pulse height fluctuates regularly while the
pulse period fluctuates regularly. As shown in FIG. 5, the pulse
height fluctuates irregularly while the pulse period fluctuates
irregularly. Accordingly, it may be determined at step 60 that the
patient is in non-REM sleep, if the calculated index varies within
a predetermined range. Further it may be determined at step 60 that
the patient is in REM sleep, if the calculated index varies
exceeding the predetermined range.
[0047] Further in the first embodiment, the sleep condition of the
patient may be detected based on the baseline of the pulse waves as
shown in FIG. 12. The baseline is a line which connects the middle
point of the pulse height of every pulse wave as shown in FIG. 3.
The baseline of the pulse waves is created instead of the envelope
A, B at step 40. Further statistical index which represents the
characteristics of baseline is calculated over and at regular
intervals at step 50. As shown in FIG. 5, the baseline fluctuates
regularly while the pulse period fluctuates regularly. As shown in
FIG. 6, the baseline fluctuates irregularly while the pulse period
fluctuates irregularly. Accordingly, it may be determined at step
60 that the patient is in non-REM sleep, if the calculated index
varies within a predetermined range. Further it may be determined
at step 60 that the patient is in REM sleep, if the calculated
index varies exceeding the predetermined range.
[0048] In the second embodiment, another attribute of the envelope
A, B of the pulse waves may be calculated instead of the amplitude
of the envelope A, B. That is, another attribute of the envelope A,
B may be employed for detecting OSA condition. When the patient is
in OSA condition, a bottom B.sub.A of the envelope A is very close
to a top T.sub.B Of the envelope B as shown in FIG. 8. In contrast
to this, a bottom B.sub.A of envelope A and a top T.sub.B of the
envelope B is not close when the patient is in eupneic condition.
Accordingly, the closeness of the bottom B.sub.A of the envelope A
and the top T.sub.B of the envelope B may be calculated and
normalized at step 50A. In this case, at step 60A, it is determined
whether the patient is in OSA condition based on the normalized
closeness of the bottom B.sub.A of the envelope A and the top
T.sub.B of the envelope B.
[0049] Furthermore an attribute of the pulse waves may be employed
for detecting OSA condition. When the patient is in OSA condition,
the tops T.sub.P and bottoms B.sub.P of the pulse waves fluctuate
largely as shown in FIG. 9. Therefore the degree of the fluctuation
of the tops T.sub.P and bottoms B.sub.P may be calculated and
normalized at step 50A, and it is determined at step 60A whether
the patient is in OSA condition based on the normalized degree of
the fluctuation of the tops T.sub.P and bottoms B.sub.P of the
pulse waves. In this case, the envelope A, B is not used at step
50A, because the tops T.sub.P and bottoms B.sub.P of the pulse
waves can be obtained without the envelope A, B of the pulse
waves.
[0050] Moreover OSA condition may be detected based on the degree
of the fluctuation of the pulse height of the pulse. FIGS. 13A-13C
show pulse waves obtained by enlarging FIGS. 8, 9 and 10 with
respect to the horizontal axis (time axis), respectively. The pulse
height of the pulse waves detected from the patient in eupneic
condition or CSA condition does not fluctuate largely.
Specifically, the pulse height of the pulse waves fluctuate within
a range of 20%. In contrast to this, when the patient is in OSA
condition, the pulse height of the pulse waves fluctuates largely.
Specifically, the minimum pulse height of the pulse waves is equal
to or lower than 50% of the maximum pulse height of the pulse
waves. Accordingly, the pulse height of every pulse wave may be
calculated at step 50A. Further a ratio of the minimum pulse height
to the maximum pulse height is calculated at step 50A. At step 60A,
it is determined that the patient is in OSA condition if the ratio
is equal to or lower than 50%.
[0051] Further the areas or lengths of the pulse waves may be
employed for detecting OSA condition. FIGS. 14A-14C show pulse
waves obtained by enlarging FIGS. 13A-13C with respect to the
horizontal axis (time axis), respectively. The area of a pulse wave
(pulse wave area) means the area formed by the pulse wave between
two bottoms and the line which connects the bottoms or formed by
the pulse wave between two tops and the line which connects the
tops as shown in FIGS. 14A-14C. The length of a pulse wave (pulse
wave length) means the length of the pulse wave between two bottoms
or two tops as shown in FIGS. 14A-14C.
[0052] The pulse wave areas of the pulse waves detected from the
patient in eupneic condition or in CSA condition do not vary
largely as shown in FIG. 14A or 14C. Specifically, the pulse wave
areas vary within a range of 20%. In contrast to this, the pulse
wave areas of the pulse waves detected from the patient in OSA
condition vary largely. Specifically, the minimum pulse wave area
is equal to or less than 50% of the maximum pulse wave area.
Accordingly, the pulse wave area of every pulse wave may be
calculated at step 50A. Further the ratio of the minimum pulse wave
area to the maximum pulse wave area is calculated at step 50A. It
is determined at step 60A that the patient is in OSA condition, if
the ratio is equal to or less than 50%.
[0053] On the other hand, the pulse wave lengths of the pulse waves
detected from the patient in eupneic condition or in CSA condition
do not vary largely as shown in FIG. 14A or 14C. Specifically, the
pulse wave lengths vary within a range of 10%. In contrast to this,
the pulse wave lengths of the pulse waves detected from the patient
in OSA condition vary largely. Specifically, the minimum pulse wave
length is equal to or less than 75% of the maximum pulse wave
length. Accordingly, the pulse wave length of every pulse wave may
be calculated at step 50A. Further the ratio of the minimum pulse
wave length to the maximum pulse wave length is calculated at step
50A. It is determined at step 60A that the patient is in OSA
condition, if the ratio is equal to or less than 75%.
[0054] Further OSA condition may be detected based on the
difference between the fluctuation of the pulse waves and
fluctuation of pulse waves detected from the patient in eupneic
condition.
[0055] In the above embodiments and modifications, the pulse wave
sensor 1 may be an ultrasonic sensor, a Doppler sensor or a
pressure type sensor.
[0056] The effects of the above embodiments and modifications are
as follows. In the first embodiment and its modifications, the
methods detect the sleep condition of the patient without executing
complicated calculations, because the regularities of the
fluctuation of the envelope, the pulse height or the baseline is
not significantly affected by the inaccuracy of the detected tops
or bottoms of the pulse waves. In this way, the methods detect the
sleep condition of the patient more simply.
[0057] Further in the first embodiment and its modifications, pulse
wave information does not need to be obtained very accurately with
respect to time. Therefore the methods can detect the sleep
condition of the patient without being significantly affected by
disturbance.
[0058] In the second embodiment and its modifications, the patient
can readily have examination at home, because a diagnosis of SAS is
made based on the pulse waves detected by the pulse sensor 1. As a
result, SAS can be detected and treated at the earliest possible
time.
* * * * *